Abundance-Indicated Subspace for Hyperspectral Classification With Limited Training Samples-Reference-Cited by-同舟云学术

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Abundance-Indicated Subspace for Hyperspectral Classification With Limited Training Samples

Published:2019-04 Issue:4 Volume:12 Page:1265-1278
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Xu Shuyuan^ORCID,Li Jun^ORCID,Khodadadzadeh Mahdi^ORCID,Marinoni Andrea^ORCID,Gamba Paolo^ORCID,Li Bo^ORCID

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Guangdong Provincial Natural Science Foundation

CIRFA under RCN

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/8686367/08674809.pdf?arnumber=8674809

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Few-Shot Open-Set Hyperspectral Image Classification With Adaptive Threshold Using Self-Supervised Multitask Learning;IEEE Transactions on Geoscience and Remote Sensing;2024

2. Forecasting Precipitation and Temperature Evolution Patterns Under Climate Change Using a Random Forest Approach With Seasonal Bias Correction;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. A Coarse-to-Fine Cell Division Approach for Hyperspectral Remote Sensing Image Classification;IEEE Transactions on Circuits and Systems for Video Technology;2023

4. Bayesian Gravitation-Based Classification for Hyperspectral Images;IEEE Transactions on Geoscience and Remote Sensing;2022

5. Hyperspectral Image Classification With Spatial Consistence Using Fully Convolutional Spatial Propagation Network;IEEE Transactions on Geoscience and Remote Sensing;2021-12

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